Articles | Volume 24, issue 1
https://doi.org/10.5194/acp-24-41-2024
https://doi.org/10.5194/acp-24-41-2024
Research article
 | 
04 Jan 2024
Research article |  | 04 Jan 2024

Utility of Geostationary Lightning Mapper-derived lightning NO emission estimates in air quality modeling studies

Peiyang Cheng, Arastoo Pour-Biazar, Yuling Wu, Shi Kuang, Richard T. McNider, and William J. Koshak

Data sets

NCEP North American Mesoscale (NAM) 12 km Analysis National Centers for Environmental Prediction, National Weather Service, NOAA, and U.S. Department of Commerce https://doi.org/10.5065/G4RC-1N91

2016v1 Emissions Modeling Platform National Emissions Inventory Collaborative http://views.cira.colostate.edu/wiki/wiki/10202

CESM2.1/CAM-chem Instantaneous Output for Boundary Conditions, Subset used Lat: 20N to 55N, Lon: 60W to 135W, May–October 2019 R. R. Buchholz et al. https://doi.org/10.5065/NMP7-EP60

Trospheric Ozone Lidar Network (TOLNet) Ozone Observational Data TOLNet Science Team https://doi.org/10.5067/LIDAR/OZONE/TOLNET

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Short summary
Lightning-induced nitrogen monoxide (LNO) emission can be estimated from geostationary satellite observations. The present study uses the LNO emission estimates derived from geostationary satellite observations in an air quality modeling system to investigate the impact of LNO on air quality. Results indicate that significant ozone increase could be due to long-distance chemical transport, lightning activity in the upwind direction, and the mixing of high LNO (or ozone) plumes.
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